Texture Classification Based on Gabor Wavelets

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Author(s):
Amandeep Kaur, Savita Gupta
Published Date:
July 05, 2012
Issue:
Volume 2, Issue 4
Page(s):
39 - 44
DOI:
10.7815/ijorcs.24.2012.038
Views:
5318
Downloads:
502

Keywords:
texture classification, mpeg-7 homogeneous texture descriptor, gabor wavelets, support vector machine, k-nearest neighbor classifier, decision tree induction method
Citation:
Amandeep Kaur, Savita Gupta, "Texture Classification Based on Gabor Wavelets". International Journal of Research in Computer Science, 2 (4): pp. 39-44, July 2012. doi:10.7815/ijorcs.24.2012.038 Other Formats

Abstract

This paper presents the comparison of Texture classification algorithms based on Gabor Wavelets. The focus of this paper is on feature extraction scheme for texture classification. The texture feature for an image can be classified using texture descriptors. In this paper we have used Homogeneous texture descriptor that uses Gabor Wavelets concept. For texture classification, we have used online texture database that is Brodatz’s database and three advanced well known classifiers: Support Vector Machine, K-nearest neighbor method and decision tree induction method. The results shows that classification using Support vector machines gives better results as compare to the other classifiers. It can accurately discriminate between a testing image data and training data.

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